Project Type: simulation model

Movement
plays a major role in shaping population densities and contact rates among
individuals, two factors that are particularly relevant for disease outbreaks.
Although any differences in movement behaviour due to individual
characteristics of the host and heterogeneity in landscape structure are likely
to have considerable consequences for disease dynamics, these mechanisms are
neglected in most epidemiological studies. Therefore, developing a general
understanding how the interaction of movement behaviour and spatial
heterogeneity shapes host densities, contact rates and ultimately pathogen
spread is a key question in ecological and epidemiological research.

In this
project, we have addressed this gap using both theoretical and empirical
modelling approaches. In the theoretical part of my thesis, we have investigated
bottom-up effects of individual movement behaviour and landscape structure on
host density, contact rates, and ultimately disease dynamics. We have extended
an established agent-based model that simulates ecological and epidemiological
key processes to incorporate explicit movement of host individuals and
landscape complexity. In the empirical part, we have focused on the
spatiotemporal dynamics of Classical Swine Fever in a wild boar population by
analysing epidemiological data that was collected during an outbreak in
Northern Germany persisting for eight years.

Diseases can have a profound impact on populations of wild animals, however, very little is known about how a dynamically (random or seasonal) changing landscape influences the interactions between host species and pathogen. I am using individual-based modelling to investigate different host-pathogen coexistence patterns under the effect of (1) dynamic resource landscapes, (2) the role of dispersal in the evolution of pathogenic virulence as well as the feedbacks of disease evolution on the evolution of movement strategies, and (3) the role of life-history trade-offs between movement strategies and infectivity as equalizing mechanism allowing for coexistence of host and pathogen.

Large changes in Earth’s climate are apparent, and there is some evidence that populations and communities respond to climate change.In order to tackle this issue, I study the effect of different levels of climatic variation on population and community dynamics, by using theoretical modelling. I also try to understand tipping points and early warning in populations and communities, by studying fluctuations in traits and demographic rates.

For large carnivores in fragmented landscapes such as the jaguar, connectivity is a conservation priority to secure population viability and genetic diversity. Management of jaguar populations requires an understanding on how the species’ movement is influenced by individual traits and the structure and configuration of their landscape. Therefore, I aim at developing a spatially explicit agent-based model of jaguar movement and population dynamics, to quantify functional connectivity and population viability in Middle America, a region which is particularly critical for jaguar connectivity and where jaguars have started exhibiting early signs of genetic isolation.

The genetic viability of the reintroduced populations of large carnivores such as Eurasian lynx (Lynx lynx) has been called into question due to the weak genetic exchange. I am developing an existing population model to include individual genetics for testing conservation management scenarios in order to reveal the potential for enhancing the genetic viability of a Central European meta-population.